Dataset Information

Changes in the geographical distribution of plant species and climatic variables on the West Cornwall peninsula (South West UK).

ABSTRACT: Recent climate change has had a major impact on biodiversity and has altered the geographical distribution of vascular plant species. This trend is visible globally; however, more local and regional scale research is needed to improve understanding of the patterns of change and to develop appropriate conservation strategies that can minimise cultural, health, and economic losses at finer scales. Here we describe a method to manually geo-reference botanical records from a historical herbarium to track changes in the geographical distributions of plant species in West Cornwall (South West England) using both historical (pre-1900) and contemporary (post-1900) distribution records. We also assess the use of Ellenberg and climate indicator values as markers of responses to climate and environmental change. Using these techniques we detect a loss in 19 plant species, with 6 species losing more than 50% of their previous range. Statistical analysis showed that Ellenberg (light, moisture, nitrogen) and climate indicator values (mean January temperature, mean July temperature and mean precipitation) could be used as environmental change indicators. Significantly higher percentages of area lost were detected in species with lower January temperatures, July temperatures, light, and nitrogen values, as well as higher annual precipitation and moisture values. This study highlights the importance of historical records in examining the changes in plant species' geographical distributions. We present a method for manual geo-referencing of such records, and demonstrate how using Ellenberg and climate indicator values as environmental and climate change indicators can contribute towards directing appropriate conservation strategies.

SUBMITTER: Kosanic A

PROVIDER: S-EPMC5798772 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Changes in the geographical distribution of plant species and climatic variables on the West Cornwall peninsula (South West UK).

Kosanic Aleksandra A Anderson Karen K Harrison Stephan S Turkington Thea T Bennie Jonathan J

PloS one 20180205 2

Recent climate change has had a major impact on biodiversity and has altered the geographical distribution of vascular plant species. This trend is visible globally; however, more local and regional scale research is needed to improve understanding of the patterns of change and to develop appropriate conservation strategies that can minimise cultural, health, and economic losses at finer scales. Here we describe a method to manually geo-reference botanical records from a historical herbarium to ...[more]

PMID: 29401494

Similar Datasets

Project description:BackgroundAlthough increasingly sophisticated environmental measures are being applied to species distributions models, the focus remains on using climatic data to provide estimates of habitat suitability. Climatic tolerance estimates based on expert knowledge are available for a wide range of plants via the USDA PLANTS database. We aim to test how climatic tolerance inferred from plant distribution records relates to tolerance estimated by experts. Further, we use this information to identify circumstances when species distributions are more likely to approximate climatic tolerance.MethodsWe compiled expert knowledge estimates of minimum and maximum precipitation and minimum temperature tolerance for over 1800 conservation plant species from the 'plant characteristics' information in the USDA PLANTS database. We derived climatic tolerance from distribution data downloaded from the Global Biodiversity and Information Facility (GBIF) and corresponding climate from WorldClim. We compared expert-derived climatic tolerance to empirical estimates to find the difference between their inferred climate niches (?CN), and tested whether ?CN was influenced by growth form or range size.ResultsClimate niches calculated from distribution data were significantly broader than expert-based tolerance estimates (Mann-Whitney p values << 0.001). The average plant could tolerate 24 mm lower minimum precipitation, 14 mm higher maximum precipitation, and 7° C lower minimum temperatures based on distribution data relative to expert-based tolerance estimates. Species with larger ranges had greater ?CN for minimum precipitation and minimum temperature. For maximum precipitation and minimum temperature, forbs and grasses tended to have larger ?CN while grasses and trees had larger ?CN for minimum precipitation.ConclusionOur results show that distribution data are consistently broader than USDA PLANTS experts' knowledge and likely provide more robust estimates of climatic tolerance, especially for widespread forbs and grasses. These findings suggest that widely available expert-based climatic tolerance estimates underrepresent species' fundamental niche and likely fail to capture the realized niche.

Project description:Season and location have previously been shown to be associated with differences in the microbiota of raw milk, especially in milk from pasture-based systems. Here, we further advance research in this area by examining differences in the raw milk microbiota from several locations across Ireland over 12 months, and by investigating microbiota associations with climatic variables and chemical composition. Shotgun metagenomic sequencing was used to investigate the microbiota of raw milk collected from nine locations (n = 241). Concurrent chemical analysis of the protein, fat, lactose, total solids, nonprotein nitrogen contents, and titratable acidity (TA) of the same raw milk were performed. Although the raw milk microbiota was highly diverse, a core microbiota was found, with Pseudomonas_E, Lactococcus, Acinetobacter, and Leuconostoc present in all samples. Microbiota diversity significantly differed by season and location, with differences in seasonality and geography corresponding to 11.8% and 10.5% of the variation in the microbiota. Functional and antibiotic resistance profiles also varied across season and location. The analysis of other metadata revealed additional interactions, such as an association between mean daily air and grass temperatures with the abundance of spoilage taxa like Pseudomonas species. Correlations were identified between pathogenic, mastitis-related species, fat content, and the number of sun hours, suggesting a seasonal effect. Ultimately, this study expands our understanding of the interconnected nature of the microbiota, environment/climate variables, and chemical composition of raw milk and provides evidence of a season- and location-specific microbiota.ImportanceThe microbiota of raw milk is influenced by many factors that encourage or prevent the introduction and growth of both beneficial and undesirable microorganisms. The seasonal and geographical impacts on the microbial communities of raw milk have been previously seen, but the relationships with environmental factors and the chemical composition has yet to be investigated. In this year-long study, we found that while raw milk is highly diverse, a core microbiota was detected for Irish raw milk, with strong evidence of seasonal and geographical influence. We also found associations between groups of microorganisms, environmental factors, and milk composition, which expand current knowledge on the relationships between microbial and chemical composition and the climate. These results provide evidence for the development of a tool to allow for the prediction of raw milk quality and safety.

Project description:Plant species distribution is constrained by both dynamic and static environmental variables. However, relative contribution of dynamic and static variables in determining species distributions is not clear and has far reaching implications for range change dynamics in a changing world. Prunus eburnea (Spach) Aitch. & Hemsl. is an endemic and medicinal plant species of Iran. It has rendered itself as ecologically important for its functions and services and is currently in need of habitat conservation measures requiring investigation of future potential distribution range. We conducted sampling of 500 points that cover most of Iran plateau and recorded the P. eburnea presence and absence during the period 2015-2017. In this study, we evaluated impacts of using only climatic variables versus combined with topographic and edaphic variables on accuracy criteria and predictive ability of current and future habitat suitability of this species under climate change (CCSM4, RCP 2.6 in 2070) by generalized linear model and generalized boosted model. Models' performances were evaluated using area under the curve, sensitivity, specificity and the true skill statistic. Then, we evaluated here, driving environmental variables determining the distribution of P. eburnea by using principal component analysis and partitioning methods. Our results indicated that prediction with high accuracy of the spatial distribution of P. eburnea requires both climate information, as dynamic primary factors, but also detailed information on soil and topography variables, as static factors. The results emphasized that environmental variable grouping influenced the modelling prediction ability strongly and the use of only climate variables would exaggerate the predicted distribution range under climate change. Results supported using both dynamic and static variables improved accuracy of the modeling and provided more realistic prediction of species distribution under influence of climate change.

Project description:Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n?=?4839) covering an extent of ?55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential for non-climate aspects of the environment to pose a constraint to range expansion under climate change.

Dataset Information

Changes in the geographical distribution of plant species and climatic variables on the West Cornwall peninsula (South West UK).

Publications

Changes in the geographical distribution of plant species and climatic variables on the West Cornwall peninsula (South West UK).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets